*Result*: Categorizing tasks around a break reduces rumination and improves task performance.

Title:
Categorizing tasks around a break reduces rumination and improves task performance.
Authors:
Chae RL; Department of Marketing, Leavey School of Business, Santa Clara University., Woolley K; Department of Marketing, Samuel Curtis Johnson College of Business, Cornell University., Sharif MA; Department of Marketing, Wharton School, University of Pennsylvania.
Source:
Journal of experimental psychology. General [J Exp Psychol Gen] 2026 Feb; Vol. 155 (2), pp. 433-450. Date of Electronic Publication: 2025 Nov 03.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: American Psychological Assn Country of Publication: United States NLM ID: 7502587 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1939-2222 (Electronic) Linking ISSN: 00221015 NLM ISO Abbreviation: J Exp Psychol Gen Subsets: MEDLINE
Imprint Name(s):
Original Publication: Washington, American Psychological Assn.
Grant Information:
Cornell University; Samuel Curtis Johnson Cornell College of Business; Wharton's Dean's Research Fund; University of Pennsylvania; Wharton School; Leavey School of Business; Santa Clara University
Entry Date(s):
Date Created: 20251103 Date Completed: 20260202 Latest Revision: 20260202
Update Code:
20260202
DOI:
10.1037/xge0001843
PMID:
41182795
Database:
MEDLINE

*Further Information*

*People often take short breaks from goal-related activities (e.g., at work, during exercise) to stay motivated and prevent burnout. The current research examines a novel factor influencing break effectiveness: task categorization. We suggest that the way people construe tasks around breaks influences their rumination about the task during the break, with consequences for postbreak performance. We test these predictions in a pilot study and five experiments. We find that when people frame a break as falling between two tasks rather than occurring in the middle of a single task, they are less likely to have negative ruminative thoughts about the task during the break (Experiments 1-3). We further examine a consequence of reducing this type of rumination: improved task performance. Using mediation (Experiment 4) and moderation (Experiment 5) approaches, we find that by reducing negative, ruminative thoughts, task categorization can improve postbreak task performance. Together, this research contributes to the literature on categorization, goal pursuit, performance, and breaks, with practical implications for reducing negative rumination. (PsycInfo Database Record (c) 2026 APA, all rights reserved).*

*

Categorizing Tasks Around a Break Reduces Rumination and Improves Task Performance

<cn> <bold>By: Rebecca L. Chae</bold>
> Department of Marketing, Leavey School of Business, Santa Clara University
> <bold>Kaitlin Woolley</bold>
> Department of Marketing, Samuel Curtis Johnson College of Business, Cornell University
> <bold>Marissa A. Sharif</bold>
> Department of Marketing, The Wharton School, University of Pennsylvania </cn>

<bold>Review of: </bold>xge0001843.pdf

<bold>Acknowledgement: </bold>Jessica D. Payne served as action editor.Data, materials, and code for Experiments 1–5, as well as preregistrations for the pilot study (https://aspredicted.org/Y43_JDH), Experiment 1 (https://aspredicted.org/SKU_GKY), Experiment 2 (https://aspredicted.org/R39_ZF2), a posttest to Experiment 3 (https://aspredicted.org/qvyk-h632), a pretest for Experiment 5 (https://aspredicted.org/XF1_3XF), and a posttest to Experiment 5 (https://aspredicted.org/jkxq-3tc3) are available on the Open Science Framework at https://osf.io/py9mk/?view_only=dd7c0b4cd93147f5a22674986624e233. The research findings have been presented at the following conferences: Society for Consumer Psychology 2022, Positive Organizational Scholarship 2022, and Association for Consumer Research 2022.The authors have no known conflicts of interest to disclose. This research was funded by the Samuel Curtis Johnson Cornell College of Business, Cornell University, awarded to Kaitlin Woolley; Wharton’s Dean’s Research Fund and Wharton School, University of Pennsylvania, awarded to Marissa A. Sharif; and Leavey School of Business’s Leavey Grant, Santa Clara University, awarded to Rebecca L. Chae. The authors are grateful to Mary Ross, Emily Hong, and Adam Chafee for data collection assistance.Rebecca L. Chae played a lead role in conceptualization, data curation, formal analysis, investigation, methodology, writing–original draft, and writing–review and editing. Kaitlin Woolley played a supporting role in formal analysis and an equal role in conceptualization, investigation, methodology, and writing–review and editing. Marissa A. Sharif played an equal role in conceptualization, investigation, methodology, and writing–review and editing.

People frequently take short breaks throughout the day. A colleague may invite them for a walk or coffee, they might receive a call from a spouse or family member, or a phone notification may prompt them to navigate away from work to check breaking news or watch a video online. New smartphone apps even allow people to precommit to breaks by scheduling them in advance and receiving reminders later in the day.

Taking breaks is typically viewed as a positive, that is, something we should be doing more of. The Centers for Disease Control and Prevention recommends that people take 5-min breaks from work every hour (Lowe et al., 2020). Taking regular work breaks is important for preventing burnout and maintaining productivity (Scholz et al., 2019). Even a TV break at work leads employees to feel more productive and better able to concentrate (Lovely, 2022). However, despite the benefits of breaks, people are more burned out than ever (Moss, 2021). Are people fully optimizing their breaks? Could the problem lie not in whether people are taking breaks but rather in how they approach and utilize them?

The current research sheds light on these questions, examining the psychological factors affecting people’s experience of their breaks. Building on research on attention, categorization, and rumination (Lieberman et al., 2022; Martin & Tesser, 1989; Van Dillen et al., 2013), we examine whether the way people construe the tasks around a break influences their break experience. Specifically, we predict that when people perceive the tasks around a break as falling into two separate categories (vs. consider the task they are taking a break from as a single activity), they will ruminate about the task less during the break, which will improve their postbreak performance.

To illustrate our prediction, consider someone who takes a break from designing research studies. They can frame the break as either in the middle of designing studies (i.e., not categorizing the task) or as falling between designing Study A and Study B (i.e., categorizing the task). We suggest that if the person categorizes the task into two separate activities, then they will be less likely to ruminate about the task during the break. Similarly, someone exercising may be less preoccupied with thoughts about their workout when taking a break if they frame their break as occurring between two different 10-min workouts (e.g., upper body and lower body) rather than in the middle of a 20-min workout. We propose that by reducing rumination during a break, categorization can help improve task performance after the break.

In what follows, we review literature supporting the benefits of breaks, as well as research on the challenge of detaching from ongoing tasks during breaks. We then unite the literature on breaks with research on task categorization to support the prediction that task categorization reduces rumination during breaks to improve postbreak performance.

<h31 id="xge-155-2-433-d71e140">Restoration and Rumination During Breaks</h31>

Breaks offer clear benefits. They help people manage stress and improve performance (Fritz et al., 2013; Sonnentag, 2003), reenergize people for the task at hand (Tyler & Burns, 2008), improve mental and physical health by reducing burnout (Westman & Eden, 1997), increase happiness (Mogilner et al., 2008), and even bolster life satisfaction (Kahneman et al., 2004).

Long breaks from work, such as vacations, improve well-being and work performance (Fritz & Sonnentag, 2006), but even smaller breaks throughout the workday are beneficial. Such breaks may be officially scheduled, such as mandatory lunch breaks (J. P. Trougakos et al., 2008, 2014) or may be more informal and unexpected, such as a microbreak between tasks (Fritz et al., 2011; J. Trougakos & Hideg, 2009). Similar to vacation time away from work, workday breaks reduce mental stress (Chong et al., 2020; Kim et al., 2017; J. P. Trougakos et al., 2008), increase creativity and engagement (Randolph, 2016), reduce errors in work performance (Ibanez & Toffel, 2020), and improve physical health (Randolph, 2016).

Breaks also benefit nonwork activities. Taking breaks reduces habituation and makes the activity more enjoyable upon returning to it (Thompson & Spencer, 1966). For example, taking breaks during exercise reduces monotony and increases workout enjoyment (Thum et al., 2017). Because enjoyment is a strong predictor of persistence in exercise (Woolley & Fishbach, 2017), breaks are an important component of pursuing and achieving fitness.

Despite these benefits, people are not always able to take advantage of the full potential of breaks. A big challenge is detaching from the ongoing task. People engaged in a task direct their attention toward the goal at hand (Ferguson & Wojnowicz, 2011; Papies & Aarts, 2016). When they take a break, they may struggle to detach from the task and instead ruminate about it (Sonnentag, 2012). Rumination is the cognitive process of repeatedly thinking about or dwelling on one’s goal strivings (Gold & Wegner, 1995), which involves automatic, intrusive thoughts (Andrews-Hanna et al., 2022) as well as controlled processes that take up cognitive capacity (Martin & Tesser, 1989). Rumination is theorized to involve both the passive activation of goal-related information in memory (i.e., spreading activation; Marsh et al., 1998) and the motivationally driven processing of goal-related information (e.g., Zeigarnik, 1938).

Rumination during breaks tends to be nonadaptive and associated with a host of negative consequences (Martin & Tesser, 1989; van Vugt et al., 2018).<anchor name="b-fn1"></anchor><sups>1</sups> During a work break, rumination may involve dwelling on whether you will be able to finish your project by the end of the day or the negative feedback you received from a supervisor (Brunstein & Gollwitzer, 1996). During an exercise break, rumination may center on feelings of tiredness and bodily pains or disappointment and self-criticism of not being able to keep up. Rumination is likely to occur when the task one is taking a break from feels unfinished, such that it continues to be cognitively active in memory (Zeigarnik, 1938).

Ruminating during a break may undermine the very purpose of breaks—to be restorative (Chong et al., 2020; Sonnentag & Fritz, 2015). We propose a solution: We predict that categorizing tasks around a break will reduce rumination about the task itself.

<h31 id="xge-155-2-433-d71e262">Task Categorization Reduces Rumination During Breaks</h31>

People frequently categorize stimuli spontaneously (Allport et al., 1954; Devine, 1989; Fiske & Neuberg, 1990). Environmental cues, such as identifying labels (Vallacher & Wegner, 1989) and arbitrary labels (Tajfel, 1959; S. Zhang & Schmitt, 1998), serve as antecedents of categorization and lead people to naturally organize their actions into distinct categories. Category labels alone can signal differences between options in a set (Mogilner et al., 2008; Redden, 2008), so the same task can be framed as a single task or two separate tasks. For example, depending on how the break is labeled, students may perceive their winter break as falling in the middle of the academic year (not categorized) or between the fall and spring semesters (categorized). Academics may consider a coffee break with a colleague as falling in the middle of writing an article (not categorized) or between writing up the introduction and the general discussion (categorized). Employees may consider a short break to watch YouTube videos as falling in the middle of their workday (not categorized) or between their 10:00–10:45 a.m. and 11:00–11:45 a.m. meetings (categorized).

Two streams of research support the prediction that categorization reduces task rumination during a break. For one, categorization shifts how people perceive the components that comprise an overall task (Sharif & Woolley, 2020). Categorization before a break leads people to perceive the task before the break as closed, with a separate task remaining. If people take a break when they perceive that the first part of the task is closed, thoughts related to the task may be less likely to interfere with the experience of the break. Even if people take a break after failing to complete a task (e.g., due to insufficient time to complete it), incorporating task categorization may improve the experience of the break by leading to the perception that this part of the task is closed off.

In addition, categorization increases psychological distance between items in different categories (Isaac & Schindler, 2014; Mishra & Mishra, 2010), which may aid in detaching from the task. For example, people exaggerate distances between items that are adjacent to category boundaries on ranked lists (Isaac & Schindler, 2014) and underestimate the likelihood of a disaster spreading to another state relative to spreading within the same state (Mishra & Mishra, 2010). By increasing perceived distance between the tasks before and after the break, categorization may allow people to better detach from the task during the break, further reducing rumination. In sum, categorizing tasks around a break may allow people to detach from the task, reducing rumination about the task during the break. Formally, we predict:
>Hypothesis 1: Categorizing tasks around a break (vs. not) will reduce rumination.

<h31 id="xge-155-2-433-d71e314">Categorization Improves Postbreak Performance</h31>

How does task categorization affect postbreak performance? We predict that by reducing rumination, task categorization can improve postbreak performance. We base this prediction on two findings from the literature: Rumination depletes cognitive resources and requires emotion regulation.

For one, rumination can undermine performance because it takes up cognitive resources (Martin & Tesser, 1989). The intrusive thoughts and mind wandering that characterize rumination (Ottaviani et al., 2015; Seli et al., 2016) are cognitively draining because they occupy attentional capacity and interfere with the goal of restorative breaks (Brunstein & Gollwitzer, 1996; Kuhl & Helle, 1986; Mikulincer, 1989). Instead of allowing the mind to rest, the mind continues to search for opportunities to complete the goal, imposing a cognitive toll (Masicampo & Baumeister, 2011). The inability to rest during a break can fatigue directed attention, prevent limited attention from being restored, and increase cognitive load, all of which harm task performance (Altmann & Trafton, 2007; Ibanez & Toffel, 2020; Paas et al., 2003). Further, because ruminative thoughts are often unwanted, people frequently try to suppress them. Suppression itself is effortful and counterproductive, depleting cognitive resources. Indeed, relative to a baseline condition, people who tried to suppress thoughts about a white bear persisted less in an unsolvable puzzle (Wegner et al., 1987). Thus, rather than restoring cognitive resources, ruminating during a break may exacerbate cognitive fatigue, impairing postbreak performance.

In addition, rumination can impair performance by increasing high-arousal negative affect, such as stress and anxiety (Pe et al., 2013; Segerstrom et al., 2000). Repetitive thoughts that comprise rumination can lead to anxiety (Segerstrom et al., 2000), and the more people struggle in updating their working memory to regulate their emotions, the more anxiety they experience from rumination (Pe et al., 2013). This high-arousal negative affect has negative consequences for performance (e.g., Morris et al., 1981). For example, experiencing everyday stress can disrupt working memory performance (Lukasik et al., 2019) and reduce both interpersonal and motivational aspects of job performance (Motowidlo et al., 1986). As a result, ruminating about one’s performance and related negative outcomes increases negative affect, lowers self-efficacy, and reduces subsequent performance (Atkinson, 1957; Bandura & Adams, 1977; Cochran & Tesser, 1996).

Thus, prior research suggests at least two pathways by which ruminating about a task during a break can undermine performance: by reducing cognitive resources and by increasing negative affect. Notably, these processes can be mutually reinforcing through the interplay of emotion and cognition (Martin & Tesser, 1989). For example, feeling stressed and anxious can be cognitively taxing as it diverts attention away from the task at hand (Houston, 1977; Morris & Engle, 1981). In addition, if taking a break is experienced as cognitively disruptive, people may deal with that discomfort by regulating their emotions (Gross, 1998). Thus, rumination can harm performance through the interplay of emotional and cognitive processes.

We propose that by reducing rumination, categorizing tasks around a break (vs. not) will improve postbreak performance. That is, people will be able to better extract the full benefits of the break when categorizing tasks (vs. not) due to reduced rumination, such that their performance will be better. Formally, we have the following hypotheses:
>Hypothesis 2: Categorization of tasks around a break (vs. not) improves postbreak performance.
>Hypothesis 3: The effect of task categorization on postbreak performance is mediated by reduced task rumination during the break.

We bring evidence for this proposed process—that is, task categorization, compared with its absence, improves postbreak performance by reducing rumination—using mediation and moderation approaches. First, we measure rumination directly, predicting that reduced rumination about the task during the break will mediate the effect of task categorization on improved postbreak performance. We then test this mechanism using process-by-moderation logic. Our theory, that is, task categorization improves postbreak performance by reducing rumination, is specific to breaks that are susceptible to rumination, which is the majority of breaks people take—passive breaks. Passive, restorative activities that people engage in during most breaks include activities like relaxing, stretching, walking, and listening to music. These passive breaks can allow people to recover from directed attention fatigue and regulate their emotions. For example, breaks involving immersion in nature require effortless attention, which allows for the restoration of the cognitive processing necessary for directed attention (Kaplan, 1995). In addition, passive activities, such as resting and relaxing, increase positive emotions, which can carry over to postbreak performance (J. P. Trougakos et al., 2008). It is for these passive breaks that are susceptible to rumination that we expect task categorization to improve postbreak performance.

However, breaks vary in how passive they are, with some breaks being more active (Fritz et al., 2013). Compared with passive breaks, active breaks, such as reading the newspaper or making personal plans, are cognitively demanding and require directed attention (Kim et al., 2017). Because active breaks like long conversations in the break room (Jett & George, 2003) or work-related socialization over lunch (J. P. Trougakos et al., 2014) use directed attention, they can be less restorative. Because active breaks demand attention, they are likely less susceptible to rumination.

We accordingly test for moderation by break type, manipulating whether people engage in a passive break activity (watching a scenic video) or an active break activity (engaging with an interactive video). If cognitively demanding breaks prevent rumination because people are fully immersed in the break activity, the effect of task categorization on rumination should attenuate. We therefore expect the effect of categorization to improve task performance after passive breaks (e.g., watching a scenic video; Keltner & Haidt, 2003; Piff et al., 2015; Rudd et al., 2012; J. W. Zhang et al., 2014), but not after active breaks (e.g., engaging with an interactive website). Formally, we predict:
>Hypothesis 4: Break type moderates the effect of task categorization on postbreak performance, such that the effect of task categorization attenuates for active breaks.

Research Overview


>

We predict that task categorization reduces rumination, which improves performance. As initial evidence for the effect of categorization on rumination, we conducted a pilot study during university students’ winter break. We expected that students nudged to categorize their academic year into semesters (vs. to consider their academic year as a whole) would ruminate less about the academic year during the study. We then tested our predictions in five experiments that utilized a paradigm that held the task and break constant. We externally assigned breaks to maintain experimental control and ensure consistency in the timing and structure of the break across conditions (Table 1 summarizes our empirics).
>
><anchor name="tbl1"></anchor>xge_155_2_433_tbl1a.gif

Experiments 1–3 tested our first hypothesis, that is, categorizing tasks around a break (vs. not) reduces task rumination during the break. We instructed people to categorize the tasks around a break (or not) when engaging in a word search paradigm (Experiment 1) and a series of exercises (Experiments 2–3). Task categorization reduced rumination during the break (Hypothesis 1), which occurred regardless of whether the break was expected or unexpected (Experiment 3).

Experiments 4–5 examined our second hypothesis, that is, categorizing tasks around a break (vs. not) improves postbreak performance, and served as a test of process. Using the word search paradigm from Experiment 1, we operationalized performance as the number of words found per minute, a measure of objective, time-bound task efficiency that captures both speed and accuracy within a structured, rule-based task. We randomly assigned participants to categorize their tasks or not, and we measured performance pre- and postbreaks. We found that categorization (vs. no categorization) improved performance after the break (Hypothesis 2). The effect of task categorization on improved postbreak performance was mediated by decreased rumination (Hypothesis 3; Experiment 4) and was moderated by whether the break itself could prevent rumination (passive vs. active break; Hypothesis 4; Experiment 5).

In addition to bringing support for our proposed mechanism, that is, rumination underlies the effect of task categorization on postbreak performance, our findings also speak against an alternative explanation based on subgoals. Possibly, task categorization influences performance not by reducing rumination, as we theorize, but by changing the structure of the task, as in research on subgoals (Huang, 2023; Huang et al., 2017). Subgoals break a salient, larger, overall goal into smaller units. As such, a subgoal increases expected goal attainment relative to an overall goal (i.e., increasing perceived feasibility of goal completion). At the same time, because subgoals focus on a smaller goal compared with the overall goal, subgoals can lower perceived goal value, making pursuit seem less desirable compared with the larger, overall goal (Huang, 2023). Consequently, subgoals are more beneficial during the initial stages of goal pursuit but are less beneficial toward the final stages of goal pursuit (Huang et al., 2017). If our categorization manipulation functioned as a manipulation of subgoals, we would expect the presence (vs. absence) of categorization to improve prebreak performance but reduce postbreak performance. Contrary to this account, we predict and find (a) no significant effect of categorization on prebreak performance and (b) a significant improvement in postbreak performance when categorization is present.

<h31 id="xge-155-2-433-d71e479">Transparency and Openness</h31>

We predetermined sample size prior to data collection based on piloting the manipulations. For all experiments involving the word search paradigm (Experiments 1, 4, and 5), we recruited 200 participants per cell to have 80% power to detect a small-to-medium-sized effect (i.e., d = .28). We recruited larger sample sizes for experiments involving the exercise paradigm as we anticipated a smaller sized effect based on piloting the manipulation. In Experiment 2, we recruited 400 participants per cell to have 80% power to detect d = .20. In Experiment 3, we did not predict a significant interaction effect. We thus increased the sample size in this experiment to 600 per cell to have sufficient power to detect a small interaction effect (<img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math1.gif"/>) and increase the likelihood of observing a significant interaction effect, if it indeed existed.

We report all data exclusions (if any), all manipulations, and all measures in each experiment. Data, materials, syntax, and preregistrations can be found on the Open Science Framework at <a href="https://tinyurl.com/bdd6dfx4" target="_blank">https://tinyurl.com/bdd6dfx4</a>. We preregistered the pilot study (<a href="https://aspredicted.org/Y43_JDH" target="_blank">https://aspredicted.org/Y43_JDH</a>), Experiment 1 (<a href="https://aspredicted.org/SKU_GKY" target="_blank">https://aspredicted.org/SKU_GKY</a>), Experiment 2 (<a href="https://aspredicted.org/R39_ZF2" target="_blank">https://aspredicted.org/R39_ZF2</a>), and a pretest for Experiment 5 (<a href="https://aspredicted.org/XF1_3XF" target="_blank">https://aspredicted.org/XF1_3XF</a>). All studies were approved by the Institutional Review Board.

Pilot Study: Categorizing the Academic Year Reduces Rumination During Winter Break


>

As an initial test of our hypothesis that categorizing tasks around a break reduces rumination during the break, we recruited university students in the middle of their winter break. We asked students to conceptualize winter break either as falling in the middle of the academic year (no-categorization condition) or as falling between two academic semesters (categorization condition). We predicted that students in the categorization condition would ruminate less when thinking about winter break than students in the no-categorization condition.

<h31 id="xge-155-2-433-d71e518">Method</h31>

<bold>Participants</bold>

We preregistered this study and recruited 126 undergraduate students through an online participant pool at a U.S. university during winter break (Mage = 21.02; SD = 4.11; 94 females, 29 males, three nonbinary).<anchor name="b-fn2"></anchor><sups>2</sups>

<bold>Procedure</bold>

We randomly assigned participants to a condition in a two-cell (no categorization vs. categorization) between-subjects design. We asked participants in the no-categorization condition to think about their winter break and how it falls during their academic year. We asked participants in the categorization condition to think about their winter break and how it falls in between two semesters of their academic year. All participants then viewed an image of the academic calendar, including their current winter break; the image reinforced the categorization versus no categorization manipulation (see Supplemental Figure S1).

To capture whether categorization reduces rumination, we then asked students to spend some time thinking about their winter break and to jot down any thoughts that came to mind about their break. Specifically, participants in both conditions read: “As a thought exercise, please spend some time thinking about your winter break. Jot down a few thoughts that crossed your mind during this thought exercise.” After this thought exercise, we asked participants to complete a three-item scale (α = .85) assessing rumination, adapted from prior research (Brunstein & Gollwitzer, 1996; Lisjak et al., 2015): “During the thought exercise you just completed, how often did you find yourself thinking about school?” “During the thought exercise, to what extent were you reminded of school?” “During the thought exercise, how much were you thinking about the challenges of performing well in school?” (0 = not at all; 100 = very much). We also explored consequences of categorization for restoration, which did not differ between conditions, possibly because this study did not control for students’ different experiences during winter break (see Supplemental Material). For all experiments, we measured demographics (age [open numeric response] and gender [choice of male, female, or nonbinary]) at the end of the survey.

<h31 id="xge-155-2-433-d71e553">Results and Discussion</h31>

In line with our prediction, participants in the categorization condition were less likely to ruminate about school work during the thought exercise (M = 52.63, SD = 27.98) than participants in the no-categorization condition (M = 64.34, SD = 23.46), t(124) = 2.54, p = .012, d = .45, providing preliminary evidence for the proposed effect.

Possibly, those in the no categorization report greater rumination because they think of more thoughts than those in the categorization condition. To address this alternative account, as an exploratory (non-pre-registered) analysis, we quantified the number of thoughts participants listed using Open AI and a research assistant coder (r = .88). We observed a marginally significant effect in the opposite direction; those in the categorization listed more thoughts than those in the no-categorization condition, AI: MCategorization = 3.14, SD = 1.37; MNo categorization = 2.69, SD = 1.44, t(124) = 1.80, p = .075; research assistant: MCategorization = 3.02, SD = 1.58; MNo categorization = 2.52, SD = 1.49, t(124) = 1.79, p = .075. Controlling for the number of thoughts listed, we continue to find that categorization reduces rumination, AI: F(1, 123) = 8.09, p = .005, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math2.gif"/>; research assistant: F(1, 123) = 7.57, p = .007, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math3.gif"/>, suggesting that our results are not due to differences in the number of thoughts listed.

Further, it is possible that participants in the categorization condition focus mainly on the future (upcoming semester), whereas those in the no-categorization condition think about the past and future (the academic year). To test for an effect of condition on temporal orientation in participants’ open responses, we used the Linguistic Inquiry and Word Count program (Pennebaker et al., 2015). This post hoc analysis did not reveal significant differences between the conditions, past: t(124) = .45, p = .655; present: t(124) = .53, p = .595; and future: t(124) = 1.30, p = .197. If anything, people used more future focused language in the no-categorization condition (M = 2.41, SD = 5.09) than the categorization condition (M = 1.41, SD = 3.49), although this did not reach statistical significance.

Having found initial evidence that categorization can reduce rumination, we next moved to a controlled experimental design that allowed us to test the prediction that task categorization reduces rumination during the break, holding the break itself constant.

Experiment 1: Categorizing Tasks Reduces Task Rumination During a Break


>

Experiment 1 examined our prediction that categorizing tasks around a break, such that the break is perceived as falling between two separate tasks (vs. in the middle of a single task), reduces rumination about the task during the break (Hypothesis 1). We tested this prediction using a word search paradigm that has been used to generalize to organizational contexts (Bohnet et al., 2016).

All participants learned that they needed to find 10 words in a word search task. They first searched for five words and then took a break with the expectation that after the break, they would search for the remaining five words (in reality, the task ended after the break). We framed the word search task as either a single task of finding 10 words (no-categorization condition) or as two separate tasks of finding five words (categorization condition). We then measured rumination about the task during the break. We predicted that categorizing tasks around the break would reduce rumination.

Furthermore, we explored the effect of categorization on the experience of two negative affective states during the break: stress and anxiety (high-arousal negative affect) and boredom (low-arousal negative affect). Because rumination increases negative affect (Lazarus et al., 1980; Morris et al., 1981), in particular, stress and anxiety (Pe et al., 2013; Segerstrom et al., 2000), we examined whether categorization reduces rumination, which in turn decreases stress and anxiety.

<h31 id="xge-155-2-433-d71e686">Method</h31>

<bold>Participants</bold>

We preregistered this study and recruited 402 U.S. participants from Amazon’s Mechanical Turk (MTurk). As preregistered, we excluded participants who did not engage in the word search task (i.e., did not find any words; clicked all letters; n = 4), leaving 398 participants (Mage = 40.49, SD = 12.86; 175 males, 221 females, and two nonbinary).

<bold>Procedure</bold>

We randomly assigned participants to a condition in a two-cell (no categorization vs. categorization) between-subjects design. In the no-categorization condition, participants learned that they would work on a “word search task,” described as a single word search puzzle in which they would need to find 10 hidden words. Participants viewed the puzzle and were instructed to start by searching on the left side of the puzzle for the first five hidden words (Figure 1, Panel A); the letters on the right side of the puzzle were unclickable and blurred. In the categorization condition, participants learned that they would work on two different puzzles, one called “Word Search Task 1” and the other called “Word Search Task 2,” each with two different sets of five hidden words. Participants started with “Word Search Task 1” (Figure 1, Panel B), which was identical to the puzzle in the no-categorization condition except for the task categorization framing.
>
><anchor name="fig1"></anchor>xge_155_2_433_fig1a.gif

Participants who initiated the word search task advanced either after they found all five words or after 5 min had passed. At this point, participants took a break from their task by watching a relaxing 45-s video of nature as seen from a train route in Switzerland (<a href="https://youtu.be/reQIWxID9JM" target="_blank">https://youtu.be/reQIWxID9JM</a>). We selected this video because it meets the criteria for a passive, restorative break, that is, it allowed participants to become immersed in nature and effortlessly listen to relaxing music, such that participants could recover from “directed attention fatigue” (Chong et al., 2020; Kaplan, 1995).

After the break, we assessed participants’ rumination during the break using a three-item scale similar to the pilot study (α = .91): “While watching the video, how often did you find yourself thinking about the word search puzzle?” “While watching the video, to what extent were you being reminded of the word search puzzle?” “While watching the video, how much were you thinking about your (potentially poor) performance on the word search puzzle?” (0 = not at all; 100 = very often/much). These items capture rumination as they focus on intrusive, repetitive thoughts, particularly those related to poor performance (Martin & Tesser, 1989; van Vugt et al., 2018).

As preregistered for exploratory purposes, we included six items assessing negative affect related to the task during the break (adapted from Van Boven & Ashworth, 2007). A factor analysis (detailed in the Supplemental Material) confirmed a two-factor structure: a four-item scale of high-arousal negative affect (i.e., stress and anxiety; α = .97), namely, “How stressed [did/will] this [past/upcoming] activity make you feel?” “How much anxiety [did/will] this [past/upcoming] activity make you feel?” and a two-item scale of low-arousal negative affect (i.e., boredom; α = .96), that is, “How boring [was/will] this [past/upcoming] activity [be]?” All items used the same 9-point scale (1 = not at all, 9 = very much). We counterbalanced whether participants first answered the items about the prior task or about the upcoming task, with no effect of counterbalancing (t &lt; 1.41). Last, we explored whether categorization affected the direction of participants’ rumination (i.e., whether it caused them to ruminate on the task they just completed or the task they had remaining). We did not find effects on these exploratory measures and report them in the Supplemental Material.

After these questions, participants learned that they would not be completing the rest of the word search puzzle. The experiment ended at that point, and participants were debriefed.

<h31 id="xge-155-2-433-d71e753">Results</h31>

<bold>Task Rumination During the Break</bold>

As predicted, participants in the categorization condition were significantly less likely to ruminate about the task during the break (M = 20.22, SD = 25.83) compared with participants in the no-categorization condition (M = 39.69, SD = 30.76), t(396) = 6.86, p &lt; .001, d = .69.

<bold>Exploratory Analysis of Negative Affect</bold>

In line with our measure of rumination, participants in the categorization condition reported significantly lower anxiety and stress (M = 2.58, SD = 2.05) than participants in the no-categorization condition (M = 3.55, SD = 2.49), t(396) = 4.28, p &lt; .001, d = .43. However, categorization had no significant effect on feelings of boredom during the break (MCategorization = 3.39, SD = 2.48; MNo categorization = 3.64, SD = 2.59), t(396) = 1.01, p = .311, d = .10. These results are consistent with research linking rumination and high-arousal negative affect (Pe et al., 2013; Segerstrom et al., 2000). Next, we tested for mediation. Rumination mediated the effect of categorization condition on stress and anxiety (βindirect = −.75, SE = .14, 95% CI [−1.03, −0.50]), based on 10,000 bootstrap samples (PROCESS Model 4; Hayes, 2012).

<h31 id="xge-155-2-433-d71e824">Discussion</h31>

Experiment 1 revealed that holding the tasks around a break, and the break itself, constant, categorizing tasks reduced rumination during the break and lowered feelings of high-arousal negative affect (i.e., reduced stress and anxiety) during the break. These findings suggest that categorization enables people to get the most out of a passive break meant to be restorative, in this case, watching a brief video of a nature scene, allowing them to ruminate less about the task during the break. This reduced rumination, in turn, also decreased feelings of stress and anxiety that arose about the task during the break.

Possibly, the beneficial effect of categorization on reduced rumination only holds when people objectively complete the task before the break. We suggest that categorization leads to the subjective perception of task completion and that the effect should generalize to situations in which people do not objectively complete the task before the break. To test this, we conducted a non-pre-registered robustness check in Experiment 1. We examined whether the effect of task categorization on rumination was contingent on participants’ completion of the prebreak task (i.e., finding all five words before the break; recall that participants advanced to the break either after finding all five words or after 5 min had passed). Importantly, a 2 (condition) × 2 (prebreak task completion) analysis of variance (ANOVA) revealed no significant interaction effect, F(1, 394) = .19, p = .660 (see additional details and Supplemental Figure S2), and a significant main effect of task categorization, F(1, 394) = 21.33, p &lt; .001, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math4.gif"/>. This result suggests that the effect of task categorization on rumination is not contingent on actual completion of the prebreak task.

Experiment 2: Categorizing Workouts Around a Break Reduces Rumination


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Experiments 2–3 tested for the generalizability of the effect of categorization on rumination by moving to a new task domain: exercise. We predicted that taking a break during a workout when framing exercise as two separate sets (vs. as a single workout) would decrease rumination about the workout during the break.

<h31 id="xge-155-2-433-d71e856">Method</h31>

<bold>Participants</bold>

We preregistered this study and recruited 798 U.S. participants via Prolific to participate in an experiment about exercising. As preregistered, we excluded participants who reported that they did not complete the workouts (n = 14), leaving 784 participants (Mage = 41.11, SD = 13.88; 358 males, 413 females, and 13 nonbinary).

<bold>Procedure</bold>

We randomly assigned participants to a condition in a two-cell (no categorization vs. categorization) between-subjects design. Participants in both conditions were tasked with completing 10 seated exercises, about 30 s each, as instructed in a series of exercise videos. In the no-categorization condition, participants saw a list of 10 exercises, labeled “Workout Exercises.” In the categorization condition, participants saw two lists of five exercises, labeled: “Workout Set 1: Arm Exercises” and “Workout Set 2: Ab Exercises.” See Figure 2 for the list of workouts. We held the actual exercises, their order, and duration constant between conditions and manipulated categorization through the label framing as in prior research (Sharif & Woolley, 2020).
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><anchor name="fig2"></anchor>xge_155_2_433_fig2a.gif

Participants took a break after the first five exercises and watched a 45-s video of a scenic train ride in Switzerland (<a href="https://youtu.be/XsVJ8PCV-0M" target="_blank">https://youtu.be/XsVJ8PCV-0M</a>), similar to that used in Experiment 1. After the break and before participants started the next five exercises, we measured task rumination during the break (three-item scale; α = .83): “While watching the break video, to what extent were you being reminded of the workout?” “While watching the break video, how often did you find yourself thinking about the workout?” “While watching the break video, how much were you thinking about your shortcomings in your performance on the workout?” (0 = not at all; 100 = very much). Similar to Experiment 1, these items capture rumination as they assess the intrusive and negative thoughts that arise about the task during the break. We included additional measures that we preregistered for exploratory purposes (see Supplemental Material). After completing these measures, participants learned that they would not be completing the remaining five exercises. We asked participants if they completed the first five workout videos; as noted earlier, we excluded participants who did not complete any workouts, which did not differ by condition (no categorization: 1.2%; categorization condition: 2.3%), χ<sups>2</sups>(1, N = 798) = 1.27, p = .260.

<h31 id="xge-155-2-433-d71e899">Results</h31>

Conceptually replicating Experiment 1, participants in the categorization condition ruminated significantly less about the workout task during the break (M = 20.47, SD = 21.44) than participants in the no-categorization condition (M = 24.49, SD = 24.11), t(782) = 2.46, p = .014, d = .18.

<h31 id="xge-155-2-433-d71e918">Discussion</h31>

Experiment 2 conceptually replicated the effect of categorization on reduced rumination during a break, this time in a different task domain—exercise (Hypothesis 1). By generalizing our effect to the exercise domain, these findings offer important practical implications for health.

Experiment 3: Categorization Reduces Rumination for Expected and Unexpected Breaks


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Experiments 1 and 2 found that categorizing tasks reduces rumination during a break. In these experiments, we did not explicitly inform participants about the upcoming break. This raises the question of whether the observed reduction in rumination as a result of task categorization is contingent on the unexpected nature of the break. Possibly, when a break is expected, the effect of task categorization on rumination attenuates. Against this account, we expected categorization to reduce rumination regardless of whether the break was expected or unexpected. This is because we predict that categorization leads people to more easily detach from their ongoing goal, which reduces rumination during both expected and unexpected breaks. We accordingly manipulated task categorization and measured rumination during the break when participants learned in advance that they would be taking a break (expected break condition) or were not told about the break until it occurred (unexpected break condition). By doing so, this study sought to determine the robustness of the task categorization effect across different break contexts.

<h31 id="xge-155-2-433-d71e926">Method</h31>

<bold>Participants</bold>

We recruited 2,387 U.S. participants via Prolific to participate in an experiment about exercising. Using the same criteria as in Experiment 2, we excluded participants who reported that they did not complete the workouts (n = 55), leaving 2,332 participants (Mage = 43.54, SD = 13.89; 1,151 males, 1,156 females, and 25 nonbinary).

<bold>Procedure</bold>

We randomly assigned participants to one of four conditions in a 2 (no categorization vs. categorization) × 2 (expected break vs. unexpected break) between-subjects design. We operationalized categorization as in Experiment 2. In the expected break condition, we informed participants at the beginning of the experiment that they would take a break during the workout at the halfway point (no-categorization condition) or in between the two sets of workouts (categorization condition). In the unexpected break condition, similar to Experiment 2, we did not inform participants until they finished the fifth exercise that they would be taking a break. In other words, as in Experiments 1–2, participants in the unexpected break conditions were not aware in advance that they would be taking a break.

All participants experienced the same break, during which they watched the 45-s video of a scenic train ride from Experiment 2. After the break, and before participants started the next five exercises, we measured task rumination during the break: “While watching the break video, how often did you find yourself thinking about the workout?” (0 = not at all; 100 = very much). Then, we told participants that they did not need to complete the second part of the workout. We asked participants if they completed the first five workouts; as noted earlier, we excluded participants who reported that they did not complete any of these workouts, which did not differ by categorization condition (no categorization: 2.6%; categorization condition: 2.0%), χ<sups>2</sups>(1, N = 2,387) = 1.25, p = .264, or break type (expected break: 2.4%; unexpected break: 2.2%), χ<sups>2</sups>(1, N = 2,387) = .17, p = .685.

<h31 id="xge-155-2-433-d71e962">Results</h31>

We conducted a 2 (task categorization) × 2 (break type) ANOVA on rumination. As predicted, this analysis revealed a main effect of task type, such that participants in the categorization condition ruminated significantly less about the task during the break (M = 33.37, SD = 29.36) than did participants in the no-categorization condition (M = 36.66, SD = 30.74), F(1, 2,328) = 6.94, p = .009, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math5.gif"/>. There was no significant effect of break type (Mexpected = 35.40, SD = 30.00; Munexpected = 34.67, SD = 30.22), F(1, 2,328) = .34, p = .560, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math6.gif"/>, or interaction effect, F(1, 2,328) = 1.77, p = .183, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math7.gif"/>. We complemented this traditional frequentist approach with a non-pre-registered post hoc Bayes analysis. Supporting our prediction, we observed a Bayes factor of BF10 = .008 for the interaction effect, which provides strong evidence in favor of the null hypothesis (Jeffreys, 1998). This, along with the nonsignificant interaction from the ANOVA, suggests that the effect of categorization on rumination did not differ for breaks that were expected (vs. unexpected).

<h31 id="xge-155-2-433-d71e1032">Discussion</h31>

Experiment 3 conceptually replicated the results of Experiments 1–2. More importantly, it demonstrated that our effect is not confined to situations wherein breaks are unexpected. Regardless of whether participants anticipated the break or not, those in the categorization condition were significantly less likely to ruminate about the task during the break compared with those in the no-categorization condition. This finding suggests that the effect of categorization on rumination is robust and operates independently of the anticipation of a break. Thus, Experiment 3 addresses the possibility that categorization reduces rumination by reducing the perception that the break is an interruption.

To further support the claim that the effect is not driven by differences in how much of an interruption the break seems, we conducted a preregistered posttest (<a href="https://aspredicted.org/qvyk-h632.pdf" target="_blank">https://aspredicted.org/qvyk-h632.pdf</a>; see Supplemental Material for full details). We asked participants the following: “To what extent did you feel that the break interrupted the exercises?” “To what extent did you perceive this break as disruptive to the exercise task?” (1 = not at all, 7 = very much; r = .89). There was no significant difference between the categorization and no-categorization conditions on perceptions of break disruption, F(1, 389) = .87, p = .352, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math8.gif"/> (see Supplemental Material for full details).

Next, we turned to a consequence of reduced rumination as a result of categorization: improved postbreak performance. To do so, we returned to the word search task paradigm, as this provides an objective measure of task performance.

Experiment 4: Categorizing Tasks Around a Break Improves Postbreak Performance by Reducing Rumination


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Experiments 1–3 found that categorizing tasks around a break reduces task rumination during the break. Building on this foundation, Experiment 4 investigated a downstream consequence of this reduction in rumination. Specifically, we tested our hypothesis, that is, task categorization improves postbreak performance (Hypothesis 2). To measure objective performance, rather than rely on self-reported measures, we returned to the word search paradigm from Experiment 1. We manipulated task categorization and measured rumination about the task during the break. Then, unlike Experiment 1, all participants completed the second half of the word search. Using this design, we were able to examine postbreak task performance, which we defined as the number of words found per minute. We predicted that participants in the categorization (vs. no categorization) condition would ruminate less about the task during the break and that this would mediate the effect of task categorization on improved postbreak performance (Hypothesis 3).

<h31 id="xge-155-2-433-d71e1073">Method</h31>

<bold>Participants</bold>

We recruited 400 U.S. participants from Prolific to complete a word search task. Following Experiment 1, we excluded participants who did not participate in the task (i.e., did not find any words; clicked on all letters; n = 5), leaving 395 participants (Mage = 33.88, SD = 10.83; 194 males, 198 females, and three nonbinary).

<bold>Procedure</bold>

We randomly assigned participants to a condition in a two-cell (no categorization vs. categorization) between-subjects design. The task proceeded similarly as Experiment 1. Those in the categorization and no-categorization conditions searched for the same 10 words, but we manipulated how the word search task was framed. In the no categorization condition, we framed the task as a single set of 10 words labeled “Word Search Task.” In the categorization condition, we framed the task as two sets of five words, labeled “Word Search Task 1” and “Word Search Task 2.”

For the first part of the word search, participants in both conditions had 5 min to search for the first five words (birthday, detective, polite, station, superficial). After they found all five words or when 5 min passed, they advanced to take a break, watching the scenic video from Experiment 1. After the break, participants in both conditions had 5 min to search for the remaining five words (available, beneficial, delicate, program, reflect).

In the no-categorization condition, for the first half of the word search, the right side of the puzzle was hidden, and participants were instructed to search on the left side of the puzzle for the first five words. For the second half of the word search, the right side of the puzzle was revealed, and participants were instructed to search on the right side of the puzzle for the remaining five words; the left side of the puzzle revealed the previous five words as found so that participants could not go back to finding the first five words. In the categorization condition, participants saw two separate word search puzzles, one for the first half of the word search and one for the second half. This design ensured that, regardless of whether participants had completed the first half of the puzzle (i.e., found the first five words), all participants in both conditions began from the same point and searched for the remaining five words after the break.

For all participants, the word search ended either when they found the last set of five words or after 5 min had passed. Participants then advanced to the remaining survey questions. Our primary measure of task performance was the number of words found per minute after the break. The task terminated after participants found all five words or after 5 min passed, so that our measure of words per minute reflects participants’ actual performance. At the end of the study, we measured task rumination during the break using the three-item scale from Experiment 1 (α = .80). We report additional exploratory measures in the Supplemental Material.

<h31 id="xge-155-2-433-d71e1099">Results</h31>

<bold>Task Rumination During the Break</bold>

Conceptually replicating Experiments 1–3, we found that categorizing tasks around a break significantly reduced rumination (MCategorization = 24.40, SD = 23.27; MNo categorization = 29.63, SD = 26.23), t(393) = 2.10, p = .037, d = .21.

<bold>Task Performance</bold>

To examine whether categorization improves postbreak performance, we conducted a repeated-measures ANOVA with timing (pre- vs. postbreak performance) as a within-subject factor and categorization condition as a between-subjects factor predicting task performance. We found a main effect of categorization (MCategorization = 2.05, SD = .78; MNo categorization = 1.82, SD = .79), F(1, 393) = 8.96, p = .003, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math9.gif"/>, and task timing, such that people improved after the break (MPrebreak = 1.66, SD = .76, MPostbreak = 2.21, SD = 1.11), F(1, 393) = 110.77, p &lt; .001, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math10.gif"/>. Importantly, these main effects were qualified by a significant interaction, F(1, 393) = 7.11, p = .008, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math11.gif"/> (Figure 3). As predicted, after the break, participants in the categorization condition performed better, finding significantly more words per minute (M = 2.40, SD = 1.10) than participants in the no-categorization condition (M = 2.02, SD = 1.11), F(1, 393) = 11.69, p &lt; .001, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math12.gif"/>. As we would expect, categorization did not affect words per minute found before the break, confirming random assignment to condition (MCategorization = 1.71, SD = .79; MNo Categorization = 1.61, SD = .74), F(1, 393) = 1.56, p = .212, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math13.gif"/>, and ruling out an alternative explanation based on subgoals.
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><anchor name="fig3"></anchor>xge_155_2_433_fig3a.gif

<bold>Mediation</bold>

We theorize that people perform better after a break when tasks are categorized (vs. not categorized) because people ruminate less about the task during the break (Hypothesis 3). Supporting our hypothesis, a mediation analysis revealed that the effect of categorization on improved postbreak performance was mediated by reduced task rumination, βindirect = .07, SE = .04, 95% CI [0.01, 0.14] (Hayes, 2012).

<bold>Alternative Explanations</bold>

Possibly, the observed effect is due to subgoals rather than task categorization. Recall that an account based on subgoals would predict that people who categorize activities around a break (vs. those who do not) would perform better at the start of an activity and that they would perform worse at the end of an activity (Huang et al., 2017). Against this account, we find no effect of condition on prebreak performance and the opposite effect on postbreak performance: Categorization, compared with its absence, improved postbreak performance.

Another possibility is that the beneficial effect of categorization on reduced rumination and improved postbreak performance only holds when one objectively completes the task before the break. Against this account, we expected that the effect of categorization would generalize to situations in which people objectively do not complete the task before the break. This is because we theorize that categorization creates a subjective sense of closure, leading people to the perception that the prebreak task is completed, even if this does not reflect reality.

We accordingly conducted robustness checks to test whether the effect of task categorization on rumination and postbreak performance was contingent on participants’ completion of the prebreak task (i.e., finding the first five words before the break). First, a 2 (categorization) × 2 (prebreak task completion) ANOVA on rumination revealed no significant interaction, F(1, 391) = .64, p = .425 (see Supplemental Figure S3a), and a significant main effect of task categorization, F(1, 391) = 4.67, p = .031, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math14.gif"/>. Second, a similar interaction predicting postbreak task performance was not significant, F(1, 391) = 1.00, p = .318 (see Supplemental Figure S3b), with a significant main effect of task categorization, F(1, 391) = 10.48, p = .001, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math15.gif"/>. These results suggest that the effect of task categorization on rumination and performance is not contingent on actual completion of the prebreak task. Furthermore, even when controlling for prebreak task completion, reduced task rumination still mediated the effect of categorization on improved postbreak performance, βindirect = .06, SE = .03, 95% CI [0.01, 0.12] (Hayes, 2012).

<h31 id="xge-155-2-433-d71e1319">Discussion</h31>

Previous research highlights the benefits of taking breaks on postbreak task performance (e.g., J. P. Trougakos et al., 2008, 2014). Advancing this research, we find that task categorization is a novel factor that can enhance postbreak performance.

As in Experiments 1–3, Experiment 4 found that categorizing (vs. not categorizing) the tasks around a break reduced rumination about the task during the break. In turn, decreased rumination resulted in improved performance on the task after the break. These results demonstrate that categorization has real consequences for behavior—task categorization allows people to more effectively avoid intrusive and ruminative thoughts during the break, such that they perform better on the task after the break than those who do not categorize their tasks.

Experiment 5: Test of Mechanism Through Process by Moderation


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We suggest that task categorization reduces task rumination during a break (Experiments 1–3) and, as a result, improves postbreak performance (Experiment 4). Experiment 5 extends these results by manipulating the type of break: passive (as in Experiments 1–4) or active, to provide a causal test for our prediction. Consistent with a process-by-moderation logic, we predicted that the effect of task categorization on postbreak performance would arise for passive breaks. While passive breaks can allow for the restoration of the cognitive processing necessary for directed attention (Kaplan, 1995) and emotion regulation (J. P. Trougakos et al., 2008), the fact that they require effortless attention necessarily means that they are most susceptible to intrusive, ruminative thoughts about the task. By contrast, active breaks that are cognitively demanding and require attention are less likely to allow for rumination during the break. For this reason, we expected task categorization to benefit performance after a passive break but that there would be no such effect of categorization for an active break (Hypothesis 4). An interaction between task categorization and break type would provide causal support for our theorized mechanism.

<h31 id="xge-155-2-433-d71e1341">Pretest</h31>

We first conducted a pretest to confirm that an active break is less susceptible to rumination relative to a passive break. Given that Experiment 4 already demonstrates that categorization reduces rumination during a passive break and improves postbreak performance, the goal of Experiment 5 was to cleanly test the interaction between break type (active vs. passive) and categorization on performance. We preregistered this pretest and recruited 381 U.S. MTurk participants (Mage = 43.15, SD = 12.68; 180 males, 197 females, four nonbinary). Using the no-categorization word search paradigm from Experiments 1 and 4, we randomly assigned participants to a passive break condition, as in prior studies, or an active break condition. This experiment proceeded similarly to Experiment 4. Participants in the passive break condition watched the same scenic video from Experiments 1 and 4, while those in the active break condition viewed and interacted with a 360-degree video tour of the Buckingham Palace (<a href="https://youtu.be/FtGN2wK9g_s" target="_blank">https://youtu.be/FtGN2wK9g_s</a>) and had to write down which rooms they entered during their virtual tour. Both breaks lasted 60 s. After the break, we measured participants’ rumination, “While watching the video, how often did you find yourself thinking about the word search puzzle?” (1 = very little, 100 = a lot), and included a manipulation check question: “Please reflect on the video you watched during the break. To what extent do you perceive the video you watched to be cognitively demanding (i.e., requiring lots of your attention)?” (1 = not at all, 7 = very much). The word search task concluded at this point.

Confirming our manipulation, participants in the active break condition perceived their break as more cognitively active (M = 4.24, SD = 1.95) than those in the passive break condition (M = 2.25, SD = 1.62), t(379) = 10.84, p &lt; .001, d = 1.11. Furthermore, those in the active break condition were less likely to ruminate about the task during the break (M = 17.65, SD = 24.83) than those in the passive break condition (M = 27.21, SD = 29.68), t(379) = 3.40, p &lt; .001, d = .35. Confirming that an active break is less likely to lead to rumination relative to a passive break, we next turned to examine the effect of categorization and break type on performance. We expected an interaction effect, such that there is a positive effect of categorization on performance for a passive break but that this effect would attenuate for an active break.

<h31 id="xge-155-2-433-d71e1394">Method</h31>

<bold>Participants</bold>

We recruited 801 U.S. participants via MTurk. We used the word search paradigm from Experiments 1 and 4 and excluded participants who did not participate in the word search task (i.e., did not find any words; clicked on all letters; n = 41), leaving 760 participants (Mage = 37.70, SD = 10.40; 478 males, 279 females, and three nonbinary).

<bold>Procedure</bold>

We randomly assigned participants to one of four conditions in a 2 (no categorization vs. categorization) × 2 (active break vs. passive break) between-subjects design. The word search task itself was identical to the task in Experiment 4. However, unlike in the previous experiments, we manipulated break type as we did in the pretest: Participants in the passive break condition watched the same scenic video from Experiment 1. Participants in the active break condition viewed and interacted with a 360-degree video tour of the Buckingham Palace and had to write down which rooms they entered during their virtual tour. Both breaks lasted 60 s.

As in Experiment 4, we measured task performance as the number of words found per minute. We also included two manipulation checks at the end of the task: “Overall, do you perceive the word search you worked on to be a single word search task or two word search tasks?” (a binary scale, to confirm the categorization manipulation) “To what extent do you perceive the video you watched to be interactive?” (1 = not at all interactive, 7 = very interactive; to confirm a difference in the attentional resources demanded by the break activities).

<h31 id="xge-155-2-433-d71e1417">Results</h31>

<bold>Manipulation Checks</bold>

A chi-square analysis confirmed the success of our categorization manipulation; significantly more participants in the categorization condition (56.3%) than in the no-categorization condition (42.0%) perceived the word search as two tasks, χ<sups>2</sups>(1, N = 760) = 15.49, p &lt; .001, φ = 14.<anchor name="b-fn3"></anchor><sups>3</sups> Moreover, participants in the active break condition perceived the break as significantly more interactive (M = 5.43, SD = 1.34) than participants in the passive break condition (M = 4.92, SD = 1.94), t(758) = 4.19, p &lt; .001, d = .30.

<bold>Task Performance</bold>

To examine whether categorization improves postbreak task performance as a function of break type, we conducted a repeated-measures ANOVA with timing (pre- vs. postbreak performance) as a within-subject variable, and categorization and break type conditions as between-subjects variables predicting task performance. This analysis revealed a nonsignificant effect of categorization, F(1, 756) = 2.35, p = .125, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math16.gif"/>; a nonsignificant effect of break type, F(1, 756) = .23, p = .635, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math17.gif"/>; and a significant effect of task timing; similar to Experiment 4, performance was higher after the break (MPrebreak = 1.19, SD = .92; MPostbreak = 1.55, SD = 1.11), F(1, 756) = 95.37, p &lt; .001, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math18.gif"/>. Importantly, we also found a significant three-way interaction, F(1, 756) = 3.90, p = .049, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math19.gif"/> (Figure 4).
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><anchor name="fig4"></anchor>xge_155_2_433_fig4a.gif

To test our prediction that break type moderates the effect of categorization on postbreak task performance, we examined postbreak task performance and found a significant Categorization × Break Type interaction, F(1, 756) = 6.90, p = .009, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math20.gif"/>. After a passive break, consistent with Experiment 4, participants in the categorization condition performed significantly better (M = 1.70, SD = 1.12) than those in the no-categorization condition (M = 1.41, SD = 1.07), F(1, 756) = 6.58, p = .011, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math21.gif"/>. By contrast, after an active break, there was no significant effect of categorization on performance (MCategorization = 1.47, SD = 1.10; MNo categorization = 1.61, SD = 1.16), F(1, 756) = 1.39, p = .239, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math22.gif"/>.

Before the break, there was no significant main effect of break type, F(1, 756) = .44, p = .506, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math23.gif"/>; categorization condition, F(1, 756) = 3.32, p = .069, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math24.gif"/>;<anchor name="b-fn4"></anchor><sups>4</sups> or Categorization × Break Type interaction, F(1, 756) = .92, p = .337, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math25.gif"/>, confirming random assignment to condition. As participants were unaware of their assigned break type prior to the break, break type indeed did not affect prebreak performance.

Similar to Experiment 4, we conducted a post hoc analysis to examine whether our findings generalize beyond objective task completion. Specifically, we tested for a three-way interaction between categorization condition, break type, and participants’ completion of the prebreak task (i.e., finding all five words before the break) on postbreak performance, which revealed a nonsignificant interaction effect, F(1, 752) = .34, p = .561, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math26.gif"/> (see Supplemental Figure S4). We continued to find our hypothesized interaction between task categorization and break type among participants who completed the prebreak task (i.e., found all five words), F(1, 419) = 4.41, p = .036, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math27.gif"/>, and those who did not (i.e., advanced to the break without finding all five words), F(1, 333) = 4.22, p = .041, <img src="http://imagesrvr.epnet.com/embimages/apa-psycarticles/xge/xge_155_2_433_math28.gif"/>.

<h31 id="xge-155-2-433-d71e1681">Discussion</h31>

Experiment 5 provides process-by-moderation evidence for the effect uncovered in Experiment 4 by manipulating break type, in support of Hypothesis 4. When the break was passive, we replicated our prior finding: Task categorization improved postbreak performance compared with its absence. When the break was active, however, task categorization had no effect on postbreak performance. Recall that break type influenced rumination during the break in the pretest to Experiment 5, such that people reported lower levels of rumination in an active (vs. passive) break. By testing for moderation by break type in Experiment 5, we suggest that categorization improves performance after a break wherein rumination is more likely (passive break), an effect that attenuates when rumination is less likely (active break). That said, it is possible that break type could have effects beyond rumination (e.g., through other differences between active and passive breaks). Notably, similar to Experiment 4, we again found that categorization enhances postbreak performance regardless of the actual completion of prebreak tasks.

General Discussion


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We find that the framing of tasks around a break affects whether people ruminate about the task during the break. Specifically, we find that categorizing the tasks around a break, such that the break is seen as falling between two tasks rather than in the middle of one task, reduces rumination during the break. The decrease in rumination in turn drives an improvement in postbreak task performance.

Students ruminated less about school during their academic break when it was framed as falling between two semesters (vs. in the middle of the academic year), people ruminated less about a word search task and experienced less stress and anxiety related to the task during the break when it was framed as falling between two separate tasks (vs. in the middle of a single task), and exercisers ruminated less about their workouts when categorizing the workouts around the break (vs. not). The effect of task categorization on reduced rumination occurs regardless of whether people anticipate the break and has consequences for postbreak performance. As evidence for this process, the effect of categorization on improved postbreak performance is stronger for passive breaks, which are more susceptible to rumination, and attenuates for active breaks.

<h31 id="xge-155-2-433-d71e1691">Theoretical Implications</h31>

Our investigation into the effect of task categorization on people’s experience of their breaks and their postbreak performance contributes to the literature on categorization, goal pursuit, and breaks. First, we introduce a novel consequence of categorization that is related to the well-studied influence of categorization on judgments of psychological distance (Isaac & Schindler, 2014; Mishra & Mishra, 2010; Sharif & Woolley, 2020; Tu & Soman, 2014; Zhao et al., 2012). We build on this research by suggesting that categorization can reduce rumination about the task during the break. We are also the first to examine consequences of task categorization for perceptions that are unrelated to the task (i.e., experience of the break).

Second, we advance research on rumination, interruptions, and goal detachment (Hunter & Wu, 2016; Liu, 2008; Masicampo & Baumeister, 2011; Sonnentag & Fritz, 2015). People are reluctant to experience interruptions the closer they are to a goal (Jhang & Lynch, 2015). They automatically suppress thoughts to minimize distractions (Fishbach et al., 2003), focusing instead on the unfulfilled goal (Moskowitz, 2002). While breaks can be beneficial in that they can cause people to take a step back and think more about the big picture (Liu, 2008), more often than not, the unfulfilled goal remains active in people’s mind, leading to increased rumination about the goal (Martin & Tesser, 1989). We find that by partitioning the ongoing goal into separate categories, categorization reduces rumination, such that thoughts about the task no longer bleed into the break (Gold & Wegner, 1995). This finding is further in line with research that finds completed intentions are less accessible than unfulfilled intentions (Marsh et al., 1998), as it is easier to stop an intention when it is perceived to be fulfilled (Bugg & Scullin, 2013).

Third, we contribute to research on attentional mechanisms affected by active goals (Ferguson & Wojnowicz, 2011; Papies & Aarts, 2016). Prior work proposes a resource matching framework whereby tasks demanding less attention can lead to disengagement (Lieberman et al., 2022). Most breaks are passive, as they are meant to allow people to restore resources necessary for directed attention. The passive nature of breaks however can backfire, leading to increased rumination, when tasks around the break are not categorized. Accordant with attention-matching frameworks, we propose that a similar process does not occur for breaks that are active. Instead, for cognitively demanding breaks, people may not have the ability to ruminate about the task—they are instead fully immersed in the break activity, such that rumination is unlikely affected by task categorization.

Finally, we answer the call for more research on conditions that influence detachment during breaks (Sonnentag & Fritz, 2015). Prior research on breaks has focused on how performance is affected by the presence (Dai et al., 2015), duration (de Salles et al., 2009), initiator (Beeftink et al., 2008), and type of break (J. P. Trougakos et al., 2008), but no research has considered the categorization of tasks around the break as a determinant of task detachment during breaks. Furthermore, most existing research focused on how to detach from work during longer breaks outside of work time (e.g., weekends and holidays), while we focus on shorter, everyday breaks.

<h31 id="xge-155-2-433-d71e1778">Practical Implications</h31>

Beyond theoretical advancements, our research offers practical implications for people’s well-being and productivity, highlighting the importance of considering the role of task categorization in break utilization strategies. Our research suggests that the same break can be experienced differently depending on how people frame the tasks around the break. Our findings thus provide a novel implication: Even with the same amount of break time, categorizing (vs. not categorizing) the tasks around a break can significantly reduce rumination about the task during the break and increase its potential as a true respite.

Our research also offers tips for people scheduling breaks. Our findings suggest it would be wise to schedule breaks between two tasks or, if this is not feasible, to frame the tasks around the break as distinct. People can easily categorize tasks using different labels for prebreak and postbreak activities (Eiser & Stroebe, 1972; Schmitt & Zhang, 1998; Tajfel, 1959) or by simply describing the tasks as unrelated (Goldstone, 1994). Indeed, in our pilot, simply instructing students to view their winter break as falling between two academic semesters, rather than in the middle of the academic year, reduced unwanted rumination about school. Even when people do not complete tasks before a break, categorizing the incomplete task as a “prebreak activity” with a subsequent “postbreak activity” could provide a sense of closure and prevent the past task from bleeding into the present break experience.

Last, people could select breaks based on the tasks they have for the day. Prior research on breaks has highlighted the restorative benefits of passive breaks, including immersion in nature or an experience of awe (Chong et al., 2020; Kaplan, 1995). One possible conclusion is that people should always choose such breaks. However, our findings call this into question—such passive breaks may not actually help improve postbreak performance if the tasks around them are not categorized.

<h31 id="xge-155-2-433-d71e1804">Avenues for Future Research</h31>

Our research offers a first step in connecting the literature on categorization, breaks, and rumination. We identify several promising avenues that follow from our initial insights. First, future research should examine moderators of this effect. As one direction, differences in task type may attenuate the effect of categorization on rumination. We focused our analysis on two types of tasks: a word search task and an exercise paradigm. We did so to provide a controlled environment and generalize between different types of tasks where people may typically take breaks. Future research should examine whether the effect holds for other types of tasks that require more complex reasoning skills. For example, tasks that rely on continuous strategic thinking may benefit from rumination during a break, such that the effect of categorization on performance attenuates. As another direction, differences in ruminative thoughts could attenuate or reverse the effect of categorization on postbreak performance. Rumination can be beneficial when it is action focused (Ciarocco et al., 2010). In such cases, thinking about the task or goal failure is productive because it helps people come up with solutions to challenges or problems. Like certain forms of procrastination, ruminating about a task during a break could lead people to think about a problem through a new lens or access remote knowledge and information that improves performance (Shin & Grant, 2021). Furthermore, some tasks may not lead to negative rumination. For example, ruminating about a fun task during a break may not be experienced negatively. In such cases, the effect of categorization on rumination could even reverse such that categorization prevents enjoyable thoughts about the task during a break. Thus, future research can examine whether the type of task or type of ruminative thought moderates the effect of categorization on rumination and performance.

Second, our research examined how categorization affects rumination and performance as a function of two types of breaks: expected (vs. unexpected) and passive (vs. active). However, more work is needed to understand whether and how break type interacts with categorization. For example, whereas we suggest that an active break attenuates the effect of categorization on postbreak performance because active breaks prevent rumination, it is also possible that an active break reduces rumination by preventing people from experiencing a restorative break in the first place. Future research could further unpack unique effects of categorization on rumination and performance as a function of break type.

Third, future research could focus specifically on how task categorization influences engagement with the break itself. In the current research, our controlled experimental design held the duration of the break constant across conditions to isolate the effect of task categorization. This was also useful from a practical perspective, as fixed breaks have many real-world parallels (e.g., 5-min coffee break; 15-min break between meetings). However, it would be fruitful to examine how task categorization might affect people’s decisions over break durations. On the one hand, people may take a longer break when categorizing the tasks around their break, as they experience fewer thoughts about their work that would otherwise prompt them to resume their prior task. On the other hand, people may take shorter breaks because the break more quickly allows them to feel refreshed and ready to get back to work.

Fourth, the current research tested one benefit of reducing rumination during a break—its immediate influence on postbreak performance. Our findings suggest that task categorization improves performance after a break by reducing rumination during the break. Future research should examine the duration of this positive influence on postbreak performance. It would also be valuable to investigate consequences of categorization on subsequent performance for extended breaks. For example, when students categorize semesters around their winter break (vs. not), they may feel more excited to return to campus or feel more prepared for the school year.

Last, task categorization may also improve postbreak performance by evoking a fresh start effect (Dai et al., 2014). This prior research found that temporal landmarks or boundaries help people perceive the postboundary period as distinct, motivating renewed effort and engagement. In our context, categorization serves as a psychological boundary between the prebreak and postbreak tasks, which may lead people to perceive the postbreak task as new. Possibly, a sense of novelty reenergizes people during the break and reduces rumination. In this way, novelty could be a downstream consequence of successful categorization, which leads to improved postbreak performance regardless of whether the prebreak task was completed.

<h31 id="xge-155-2-433-d71e1825">Constraints on Generality</h31>

The primary questions tested in the current research were as follows: (a) Does categorization influence rumination, and if so, (b) what are the implications of this for performance? Building on prior research, we theorized that reduced rumination from task categorization could improve postbreak performance for several reasons, such as reduced cognitive resources and/or increased negative affect. Although we provided empirical support for negative affect, empirically testing other potential antecedents of rumination is beyond the scope of the current research and remains an open question for future research to examine.

In our experiments, we manipulated task categorization across two different paradigms—word search and exercise. Future research should examine whether the benefits of categorizing tasks around breaks generalize to other types of tasks. We also included a break in the middle of the task, based on a pilot study demonstrating that this is where most people prefer a break (see Supplemental Material). However, it is an open question whether our effects would hold for earlier, later, or multiple breaks. For example, the effects of categorization may be amplified when breaks occur at a natural stopping point (e.g., halfway through a task). On the other hand, excessive fragmentation (e.g., introducing 10 breaks) might increase fatigue and mental strain due to constant transitions, which could diminish the restorative benefits of breaks. It is an open question whether such overfragmentation might disproportionally affect people who do versus do not categorize tasks around a break. We also assigned participants to take a break. Although we generalize our findings to expected and unexpected breaks, it is an open question whether these effects hold when the break is internally decided upon rather than externally given.

In our experiments, participants could not resume the prebreak task after the break. Because some participants completed the task before the break while others did not, allowing participants to return would have compromised the study’s design. Thus, it is an open question whether the effects generalize to situations where people can revisit the first part of the task. However, given that our effects hold even when participants do not complete the prebreak task, we suspect they would generalize.

Last, our studies involved students at a U.S. university and online U.S. MTurk and Prolific participants. While we manipulated the presence or absence of categorization to ensure controlled experiments, individuals may differ in how much they spontaneously categorize tasks around a break. It is an open question whether such individual differences influence people’s break experience and postbreak task performance. In addition, whether our findings generalize to individuals in non-Western, educated, industrialized, rich, and democratic cultures remains an open question. Past research suggests that culture influences categorization styles, with more individualistic (vs. collectivistic) thinking encouraging a focus on objects and their proper categorization (Knight & Nisbett, 2007; Nisbett et al., 2001). Future research can examine whether the categorization effect we observe extends to other cultural contexts.

<h31 id="xge-155-2-433-d71e1844">Conclusion</h31>

Breaks are known to improve task performance, yet we find that the way people construe tasks around the break is also of consequence. When people struggle to detach from an ongoing task, and thus ruminate about the task during the break, the break does not allow for a mental reset. We offer a solution: categorizing tasks around the break. Task categorization leads to less task rumination during the break itself, which improves postbreak performance. Thus, the next time you get a break, make sure to frame it as falling between two separate tasks rather than in the middle of a single, ongoing task. Doing so will lead you to ruminate less, and possibly perform better, as a result.

Footnotes

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<sups> 1 </sups> This is not to say that all rumination is nonadaptive. Task-focused thoughts directed at how to correct failure can be beneficial (Ciarocco et al., 2010), a point we return to in the General Discussion section.

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<sups> 2 </sups> We recruited participants up to the preregistered threshold. As preregistered, this sample excluded nonstudents (alumni, staff); results remain significant when including all participants in the analysis (n = 209).

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<sups> 3 </sups> Although this manipulation check was significant, a large portion of participants in the categorization condition perceived the task they worked on as a single word search task, possibly due to the subtle nature of the categorization label manipulation and because we asked this question at the end of the survey. To provide stronger evidence of this manipulation, we conducted a preregistered posttest (<a href="https://aspredicted.org/jkxq-3tc3.pdf" target="_blank">https://aspredicted.org/jkxq-3tc3.pdf</a>) to Experiment 5 reported in full in the Supplemental Material, where we asked participants: “When you were taking the break, to what extent did you think of the work you did before the break as on-going versus partitioned?” (1 = ongoing; 7 = partitioned). Confirming our manipulation, participants in the categorization condition perceived the task as significantly more partitioned (M = 4.61, SD = 1.94) than those in the no-categorization condition (M = 3.90, SD = 2.10), t(195) = 2.51, p = .013, d = .36.

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<sups> 4 </sups> The marginally significant effect of categorization on prebreak task performance indicated that participants in the categorization condition performed slightly better even before the break, which was not hypothesized. We observed a Bayes factor of BF10 = 0.446, indicating anecdotal evidence in favor of the null hypothesis (Jeffreys, 1998); the data are approximately 2.24 times more likely under the null than the alternative. Given this, and the absence of prebreak differences in Experiment 4, we do not believe that this is a reliable effect. Possibly, categorizing tasks before a break may initially motivate performance at times, but this requires further investigation.

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Submitted: June 10, 2024 Revised: June 18, 2025 Accepted: July 23, 2025

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